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Previous studies demonstrate that the use of artificial intelligence (AI) dialogue systems for English as a Foreign Language (EFL) education has effectively improved university students' reading, writing, and listening abilities. However, there are limited systematic reviews focused on the evidence-based interactional competence of EFL university students. This study aims to examine the use of AI dialogue systems to enhance EFL university students' interactional competence. Through the PRISMA process, this study identified 28 articles published between January 2013 and August 2022 in journals and conferences from the most popular databases, including Google Scholar, ProQuest, IEEE, ScienceDirect, and Web of Science. The systematic review identified six dimensions and 25 sub-dimensions that influence the application of AI dialogue systems for EFL learning. The six dimensions include technological integration, task designs, students’ engagement, learning objectives, technological limitations, and the novelty effect. Gaps are identified that (1) components of debate and problem-solving skills in EF acquisition in university education seemed to be overlooked in the AI dialogue system design, and (2) the importance of embedding culture, humor and empathy functions were not taken into consideration in the AI dialogue system. This study finds that the development and implementation of an AI dialogue system in EFL is still in its infancy stage. Future research should emphasize meaning-based communication, intelligibility in language competency, debate, and problem-solving skills in university education.
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Chunpeng Zhai
Santoso Wibowo
SHILAP Revista de lepidopterología
Computers and Education Artificial Intelligence
Central Queensland University
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Zhai et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69dc337c3080d3567e2748d2 — DOI: https://doi.org/10.1016/j.caeai.2023.100134